肾透明细胞癌m6A甲基化修饰相关的lncRNA预后模型的构建与应用

Identification and application of an effective N6-methyladenosine-related lncRNA prognostic model for clear cell renal cell carcinoma

目的利用TCGA数据库建立肾透明细胞癌(ccRCC)N6-甲基腺嘌呤(m6A)甲基化修饰相关的长链非编码RNA(lncRNA)预后模型,并探讨其临床意义。方法从TCGA数据库中获取ccRCC的转录组数据和临床数据,通过Pearson相关性分析及单因素Cox回归分析筛选与m6A表达及预后相关的lncRNA。将配有完整生存资料的数据随机分为训练集和验证集,训练集采用LASSO回归分析确定关键lncRNA并构建预后模型、计算风险评分。根据风险评分的中位值将训练集的患者分为高、低风险两组,绘制Kaplan-Meier生存曲线比较两组生存差异。将预后模型及临床病理参数纳入单因素和多因素Cox回归分析,构建列线图预测ccRCC患者3年及5年总生存率。并用验证集对预后模型进行验证评估。结果共筛选出12个m6A相关的关键lncRNA(AC009948.2、AC011752.1、AC018752.1、AF117829.1、AL008718.3、AL133243.3、AL158071.5、COL18A1-AS1、DLEU2、LINC00115、RPL34-AS1及SNHG10)构建预后模型。训练集Kaplan-Meie r生存曲线显示高风险组患者的总体生存期明显低于低风险组(P<0.001),并在验证集得到一致的结果(P<0.001)。多因素Cox回归分析显示年龄、肿瘤分级、临床分期及预后模型是ccRCC患者预后的独立影响因素(P<0.01)。以预后模型及临床病理特征联合构建的列线图具有良好的区分度和一致性。结论m6A相关的lncRNA预后模型能够预测ccRCC患者的预后,有望为患者的个体化治疗提供新的参考依据。

Objective To establish an N6-methyladenosine(m6A)-related long non-coding RNA(lncRNA)prognostic model for clear cell renal cell carcinoma(ccRCC)using TCGA data and to explore its clinical significance.Methods The transcriptome and clinical data of ccRCC were extracted from the TCGA database.Prognostic m6A-related lncRNAs were screened using Pearson correlation analysis and univariate Cox regression analysis.The data with complete survival informat were randomly divided into training set and validation set.In the training set,important and m6A-related lncRNAs were identified with LASSO regression analysis to construct a prognostic model,and the risk score of each patient was calculated,based on which the patients were divided into high-and low-risk groups.Kaplan-Meier survival curve was drawn to compare the survival difference between the two groups.The independent predictive value of the model and clinicopathological parameters were analyzed with univariate and multivariate Cox regression.A nomogram was constructed to predict the 3-and 5-year overall survival.Finally,the model was validated in the validation set.Results A total of 12 m6A-related lncRNAs were selected to establish the model,including AC009948.2,AC011752.1,AC018752.1,AF117829.1,AL008718.3,AL133243.3,AL158071.5,COL18A1-AS1,DLEU2,LINC00115,RPL34-AS1 and SNHG10.Kaplan-Meier survival analysis in the training set showed that the overall survival of patients in the high-risk group was significantly lower than that of the low-risk group(P<0.001),and consistent results were confirmed in the validation set(P<0.001).Multivariate Cox regression analysis showed that age,tumor grade,clinical stage and prognostic model were independent influencing factors of prognosis(P<0.01).The nomogram showed good discrimination and consistency.Conclusion This prognostic model is able to predict the prognosis of ccRCC patients and may be useful for designing individualized treatment strategies.